Artificial neural networks for compound semiconductor device modeling and characterization-Reference-Cited by-同舟云学术

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Artificial neural networks for compound semiconductor device modeling and characterization

Published:2017-10 Issue: Volume: Page:
ISSN:
Container-title:2017 IEEE Compound Semiconductor Integrated Circuit Symposium (CSICS)
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Author:

Xu Jianjun,Root David E.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8211425/8240418/08240446.pdf?arnumber=8240446

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Modern Framework to Incorporate Measured Load Pull Data in Power Amplifier Design;2024 IEEE Wireless and Microwave Technology Conference (WAMICON);2024-04-15

2. Artificial Neural Networks for GaN HEMT Model Extraction in D-band Using Sparse Data;2023 IEEE Radio Frequency Integrated Circuits Symposium (RFIC);2023-06-11

3. A Review of Circuit Models for GaN Power Devices;2023 IEEE 6th International Electrical and Energy Conference (CIEEC);2023-05-12

4. PACOSYT: A Passive Component Synthesis Tool Based on Machine Learning and Tailored Modeling Strategies Towards Optimal RF and mm-Wave Circuit Designs;IEEE Journal of Microwaves;2023-04

5. Procedural- and Reinforcement-Learning-Based Automation Methods for Analog Integrated Circuit Sizing in the Electrical Design Space;Electronics;2023-01-06

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